Optical data-reading systems have become an important and ubiquitous tool in tracking many different types of items, and machine-vision systems have become an important tool for tasks such as part identification and inspection. Both optical data-reading systems and machine vision systems capture a two-dimensional digital image of an optical symbol (in the case of an optical data-reading system) or a part to be inspected or analyzed (in the case of a general machine-vision system) and then proceed to analyze that image to extract the information contained in the image. One difficulty that has emerged in both types of systems is that of ensuring that the optics used to capture images have the correct field of view, depth of field and working focal distance for the application in which they are or will be used. Without optics having the correct characteristics for an application, it can be difficult or impossible for the system to capture images that can be analyzed.
In some cases, a customer that buys an imaging system doesn't know ahead of time what the required field of view, depth of field and working focal distance will be. In other cases, the customers' requirements are such that the field of view, depth of field and working focal distance are highly variable. In either case, with imaging systems having fixed-focus optics the customer would be forced to buy multiple systems to be able to fit one to their need. Imaging systems with zoom lenses have emerged as one solution, but these have drawbacks as well. A given zoom lens may not have the needed combination of field of view, depth of field and working focal distance. Zoom lenses are also complex, expensive, and have many moving parts that generate debris that can contaminate elements within the imaging system, such as the image sensor, and can lead to decreased system performance.